class_docstr: Simple Stage that stack GNN layers
code: def forward(self, batch):
      for layer in self.children():
          batch = layer(batch)
      if cfg.gnn.l2norm:
          batch.node_feature = F.normalize(
              batch.node_feature, p=2, dim=-1
          )
      return batch
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  import graphgym.register
  from graphgym.config import cfg
  from graphgym.init import init_weights
  from graphgym.models.act import act_dict
  from graphgym.models.feature_augment import Preprocess
  from graphgym.models.feature_encoder import edge_encoder_dict, node_encoder_dict
  from graphgym.models.head import head_dict
  from graphgym.models.layer import BatchNorm1dEdge, BatchNorm1dNode, GeneralLayer, GeneralMultiLayer
label_desc: Use image node_id 2 for calling the GNNStackStage obj's underlying member method code with example usage: obj.forward(batch) and returns: batch